A geologic model is a computer-based representation of a subsurface earth volume, such as a petroleum reservoir or a depositional basin. In the oil and gas industry, geologic models are commonly used in activities such as determining the locations of wells, estimating hydrocarbon reserves, or planning reservoir-development strategies. Geologic models are commonly inputs to production flow simulations that are used to test development and production scenarios in order to optimize return on investment. A key parameter in flow simulation is the spatial distribution of permeability, which together with the properties of the hydrocarbons and other fluid found in the subsurface reservoir, determines the producibility of the reservoir.
The geologic modeling process can use many different data types, including but not limited to rock-property data obtained from wells and seismic data, as well as structural and stratigraphic surfaces that define distinct regions within the model. The goal of the process is to construct a representation of the subsurface that is realistic, accurate, and consistent with the available data types.
Geologic models may take on many different forms. Most commonly, descriptive or static geologic models built for petroleum applications are in the form of a three-dimensional array of model blocks (cells), to which geologic and/or geophysical properties such as lithology, porosity, acoustic impedance, permeability, or water saturation are assigned (such properties will be referred to collectively herein as “rock properties”). The set of cells constitutes the geologic model and represents the subsurface earth volume of interest. Dimensions of the cells are commonly chosen so that the rock properties within a cell are relatively homogeneous without creating an excessive number of cells. The goal of the geologic modeling process is to assign rock properties to each cell in the geologic model so that the resulting model is an accurate representation of the subsurface earth volume of interest.
There are two main ways to populate the discretized geologic volume with properties-geocellular techniques and object-based modeling. In the geocellular approach, geostatistical estimation methods (which may be either deterministic or probabilistic) are commonly used. These methods take into account distance, direction, and spatial continuity of the rock property being modeled. Deterministic estimation methods typically calculate a minimum-variance estimate of the rock property at each block. Probabilistic estimation methods develop distributions of the rock-property values and produce a suite of geologic models for the rock property being modeled, with each model theoretically being equally probable. The spatial continuity of a rock property may be captured by a variogram. A variogram is a well-known technique for quantifying the variability of a rock property as a function of separation distance and direction. Geostatistical models offer several key advantages in that they can utilize a wide range of existing statistical algorithms, readily accommodate data control points such as wells, and are amenable to rock property modeling and optimization using geophysical constraints such as, three-dimensional seismic data. U.S. Pat. Nos. 5,838,634, 6,381,543 and 6,480,790 cover geocellular modeling methods embodied in processing flows which include repetitive optimization steps to drive the geologic model toward conformance with geologic and geophysical data, such as well logs, seismic surveys and subsurface fluid production and pressure data. Most commercial geologic modeling software packages, including PETREL, GOCAD and STRATAMODEL, contain a wide spectrum of geostatistical tools designed to fulfill the requirements of the reservoir geologist or engineer.
The chief drawback to geocellular models is that they generally do not closely replicate structures observed in depositional systems such as rivers, deltas and deep-water canyons and fans. This consideration is significant in that the internal structure of the depositional system may have a significant effect on reservoir quality and continuity.
Object-based geologic models treat subsurface reservoir volumes as assemblages of geologic objects such as channels or depositional lobes. U.S. Pat. No. 6,044,328 discloses one object-based modeling scheme that allows a geologist or reservoir engineer to select geologic objects from an analog library to best match the reservoir being modeled. The appropriateness of the analog is judged by the operator of the process based on their geologic experience. Most commercial software packages, including PETREL, IRAP-RMS and GOCAD implement objects as volumetric elements that mimic channels and lobes using simplified elements based on user-deformable shapes such as half pipes and ellipses.
Object-based modeling is most useful where three-dimensional spatial information such as that provided by three-dimensional seismic volumes is lacking or is of low resolution. The simple shapes provided in existing methods can not readily capture the complex spatial information seen in modern three-dimensional seismic surveys. Furthermore, most of the current techniques emphasize channels and channel complexes as the primary reservoir element. While channelized systems are significant hydrocarbon reservoir types, the identification or modeling of channels is incomplete without accurately characterizing the potentially porous and permeable sands that fill them. The sands themselves are packaged in lobate bodies much like sand bars observable in modern rivers or deltas. It is these bodies which form the bulk of siliciclastic reservoirs. Geologic models that honor and take advantage of these naturally occurring, fundamental elements should produce more accurate subsurface models.
Process-based geologic modeling tools attempt to reproduce subsurface stratigraphy by simulating or approximating the physical processes of sediment transport and deposition, building sedimentary deposits in chronological order. The simulation results can be checked against subsurface data and the simulation rerun using new control variables in an iterative process until approximate correspondence with subsurface data is achieved. U.S. Pat. Nos. 5,844,799, 6,205,402 and 6,246,963 describe three such methods which employ diffusion or rule-based process models to create basin-scale models with limited spatial detail.
Process-based models can typically generate realistic-looking simulated deposits, but they are not commonly used for commercial geologic modeling because it is difficult to adjust the model inputs in such a way as to cause the simulated deposit to honor subsurface data constraints. Unlike geocellular or object-based models, process-based models typically cannot be efficiently optimized by computer algorithms when new static or dynamic data become available. Finally, modern three-dimensional seismic surveys provide a spatial framework for geologic models which is difficult to replicate with process-based models.
From the foregoing, it can be seen that there is a need for a method that honors the shapes and property distributions of naturally occurring sedimentary deposits but can also be easily tied to available seismic and well data. In the above described method, process-based, object-based and geostatistical approaches may be utilized. Preferably, the method may provide an automated optimization process capable of being performed by a computer, resulting in a more accurate model of the subsurface earth volume of interest with minimal additional time and effort. The present invention satisfies this need.